Do ethical values buffer against workplace stressors? Interactive effects of challenge-hindrance stressors and Islamic work ethics on individualized change outcomes ( <i>¿Constituyen los valores éticos un factor de amortiguación frente a los estresores laborales? Efectos interactivos de los estresores obstáculo y la ética laboral islámica en los resultados de cambio individual</i> )
Bibliographic record
Abstract
Drawing on social exchange theory, this study investigated the impact of workplace stressors on creativity and job burnout among engineers. Moreover, it also investigated the conditional role of Islamic work ethics in the above relationships. For testing the hypotheses, data from 161 engineers and their respective managers were collected using a time-lagged approach from various organizations in Pakistan. Further, a structural equation modelling technique was utilized for testing the proposed relationships. The findings suggested a positive impact of challenge and hindrance stressors on employees’ burnout. Moreover, challenge and hindrance stressors were found to have a negative impact on employees’ creativity. Finally, the results supported a conditional role of Islamic work ethics in the relationships of challenge stressors with creativity and job burnout. While existing literature has focused on the work-related outcomes of workplace stressors, this research has simultaneously incorporated the role of work and non-work factors. Finally, the integration of Islamic work ethics provided a novel perspective for understanding how employees’ values and beliefs facilitate effectively managing their behavioural and attitudinal outcomes, particularly under stressful circumstances.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".